Make sense of the numbers, methods and conclusions.
I help university students understand the statistics and quantitative methods used in their course, from probability and descriptive statistics to inference, regression and interpretation.
Statistics inside many different degrees.
You may be taking a dedicated statistics course or a quantitative methods course inside another degree. We can work from the exact topics and methods your course requires.
Work through the method and what it means.
Different courses use different combinations of topics. These are examples of areas I can support where they are part of your syllabus.
Describing data
Data types, tables, graphs, measures of centre, spread and the basic ideas needed before formal inference.
Reason about uncertainty
Probability rules, conditional probability, random variables and common distributions where they appear in the course.
Draw conclusions from samples
Sampling ideas, confidence intervals, hypothesis tests, assumptions and interpretation of results.
Correlation and regression
Understanding relationships between variables, fitting simple models and interpreting coefficients and output.
Course-specific calculations
Mathematical and statistical methods used in business, finance, science, health and other quantitative courses.
Explain the result in context
Move from formulas and software output to a conclusion that answers the question being asked.
The calculation is only part of the problem.
Statistics often becomes difficult when students can follow a formula but are unsure which method to choose, what assumptions are being made, or how to interpret the final result.
We can slow that process down and connect the question, method, calculation and conclusion.
A useful way to work
- Identify the type of question
- Choose an appropriate method
- Check the assumptions
- Carry out the calculation carefully
- Interpret the result in context
Bring the statistical output you are expected to interpret.
If your course uses software or produces statistical output, we can work on understanding what the output says rather than treating it as a collection of numbers.
The focus remains on the mathematics and statistics behind the result and on interpreting it correctly.
Useful things to send
- Course name and code
- Syllabus or topic list
- The method currently being studied
- An example of the output or question format
- Any upcoming test or exam
Tell me which statistics or quantitative methods course you are taking.
Send the course title, topic list or syllabus and I can check whether I cover the methods you need.